基于短文本的独立语义特征抽取算法

提出了一种基于短文本的独立语义特征抽取算法，旨在降低文本向量的稀疏性并提其高语义表示能力。该算法首先采用潜在语义分析降低文本的维数并去除噪声，然后运用独立成份分析方法在潜在语义特征中提取出最能表达语义且相互统计独立的特征。实验表明此算法优于潜在语义索引算法。

Independent semantic feature extraction algorithm based on short text

An independent semantic feature extraction algorithm was proposed, aiming at reducing the sparseness of short text and enhancing its capability of semantic expression. The algorithm first makes use of latent semantic indexing to reduce the dimension and wipe off noise, and then it introduces independent component analysis to extract statistic independent and semantic features. Experimental results prove the feasibility of the algorithm and demonstrate it is superior to latent semantic indexing.